Fat pads dynamically regulate energy storage capacity under energy excess and deficit. This remodeling process is not completely understood, with controversies regarding differences between fat depots and plasticity of adipose cell number. We previously examined changes of mouse adipose cell-size distributions in epididymal, inguinal, retroperitoneal, and mesenteric fat under both weight gain and loss. With mathematical modeling, we specifically analyzed the recruitment, growth/shrinkage, and loss of adipose cells, including the size dependence of these processes. We found a qualitatively universal adipose tissue remodeling process in all four fat depots: (1) There is continuous recruitment of new cells under weight gain; (2) The growth and shrinkage of larger cells (diameter > 50 microns) is proportional to cell surface area; and (3) Cell loss occurs under prolonged weight gain, with larger cells more susceptible. The mathematical model gives a predictive integrative picture of adipose tissue remodeling, and can be used to examine changes in the relative importance of these specific cellular processes in obesity and diabetes. In previous publications, we demonstrated that there appeared to be a periodicity in changes in the cell-size probability distributions by analyzing longitudinal data from two Zucker fatty rats. In that work, we proposed a mathematical model that could give rise to such periodicity, and a prediction of that model was that a high-fat diet may lead to a decrease in the period, relative to chow. We take two very different models, the body composition model of Hall and colleagues, and a model of adipose tissue dynamics, and integrate them. This is not a facile exercise. Indeed, one might wonder that it is possible at all, for the Hall model predicts fat mass loss or gain depending on diet but with no dependence on insulin resistance. On the other hand, it is well-known from the work of Arner and colleagues, McLaughlin and colleagues, and others, that adipose tissue state is correlated with insulin resistance. We resolve this puzzle with dynamical modeling. We show that the adipose tissue dynamics that is implied by requiring consistency between adipose tissue state and body composition by matching fat mass loss and gain in the two models at tissue and organism scales predicts that insulin resistant individuals have lower rates of lipolysis and higher rates of lipogenesis. This result is obtained without any insulin dependence in either the body composition model or the adipose tissue dynamic model.